code: def bundle_spaces(request):
      if isinstance(request.param, int):
          n = k = request.param
      else:
          n, k = request.param
      request.cls.base = PSDMatrices(n=n, k=k, equip=False)
      request.cls.total_space = total_space = FullRankMatrices(
          n=n, k=k, equip=False
      )
      total_space.equip_with_metric(MatricesMetric)
      request.cls.bundle = BuresWassersteinBundle(total_space)
  
imports: import random
  import pytest
  from geomstats.geometry.full_rank_matrices import FullRankMatrices
  from geomstats.geometry.matrices import MatricesMetric
  from geomstats.geometry.rank_k_psd_matrices import BuresWassersteinBundle, PSDBuresWassersteinMetric, PSDMatrices, RankKPSDMatrices
  from geomstats.test.parametrizers import DataBasedParametrizer
  from geomstats.test.random import RankKPSDMatricesRandomDataGenerator
  from geomstats.test_cases.geometry.fiber_bundle import FiberBundleTestCase
  from geomstats.test_cases.geometry.manifold import ManifoldTestCase
  from geomstats.test_cases.geometry.mixins import ProjectionTestCaseMixins
  from geomstats.test_cases.geometry.quotient_metric import QuotientMetricTestCase
  from .data.rank_k_psd_matrices import BuresWassersteinBundleTestData, PSD22BuresWassersteinMetricTestData, PSD33BuresWassersteinMetricTestData, PSDBuresWassersteinMetricTestData, RankKPSDMatrices32TestData, RankKPSDMatricesTestData
label_desc: Use image node_id 3 for calling a global function with example usage: bundle_spaces(request) without return types